India Unveils Full-Stack AI Strategy to Challenge Global Tech Dominance

The unveiling of India’s full-stack AI strategy marks a pivotal shift in the global technological landscape. At the AI Impact Summit 2026, Union Minister Ashwini Vaishnaw articulated a vision that moves beyond the traditional 'back-office' identity of the Indian IT sector. By targeting five critical layers—applications, models, chips, infrastructure, and energy—India is attempting to build a self-sustaining ecosystem that prioritizes sovereignty and scalability. This 'whole-of-nation' approach is designed to insulate the domestic economy from over-reliance on foreign foundational models while positioning Indian firms as leaders in the emerging AI-as-a-Service (AIaaS) market.

The services layer represents the most immediate transformation for the SaaS and Cloud sectors. India’s IT behemoths, including TCS, Infosys, Wipro, and HCLTech, are undergoing a massive structural realignment. No longer content with legacy software maintenance, these firms are embedding generative AI and agentic workflows into their core offerings. The scale of this transition is underscored by the collective reskilling of over one million employees. This workforce evolution is essential for India to maintain its dominance in global IT exports, which are expected to be redefined by AI-driven delivery models over the next decade. By moving toward agentic workflows, these companies are shifting from labor-intensive models to high-margin, outcome-based AI services.

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India’s IT behemoths, including TCS, Infosys, Wipro, and HCLTech, are undergoing a massive structural realignment.

On the model layer, the launch of BharatGen Param2, a 17-billion parameter model supporting 22 Indian languages, signals a commitment to linguistic inclusivity that global models often overlook. While giants like OpenAI and Google maintain a lead in raw scale, the Indian strategy focuses on 'frugal' and 'sovereign' AI. Startups like Sarvam AI and Krutrim are leading this charge, focusing on Indic language optimization and cost-efficient inference. This localization is not just a cultural preference but a strategic necessity for public sector adoption and domestic enterprise security, where data sovereignty is paramount. The goal is to provide viable, affordable alternatives for domestic use cases that require deep understanding of local context and dialects.

The semiconductor and infrastructure layers are perhaps the most ambitious components of the roadmap. Under the Semicon 2.0 mission, India is transitioning from a design-heavy services model to a comprehensive fabrication and packaging powerhouse. This shift is critical for securing the hardware supply chain necessary to power the next generation of GPUs and AI accelerators. By integrating energy strategy into the AI roadmap, the government acknowledges the massive power demands of modern data centers. This holistic view—linking the silicon in the chip to the electrons in the grid—sets the Indian roadmap apart from purely software-focused national strategies, ensuring that infrastructure growth is paired with sustainable energy solutions.

Looking forward, the success of this strategy will depend on the seamless integration of these five layers. If India can successfully bridge the gap between its world-class software talent and its nascent hardware manufacturing capabilities, it could emerge as the primary alternative to the US-China AI duopoly. The focus on 'frugal' AI—achieving high performance with fewer parameters and lower compute costs—could also make Indian technology highly attractive to other emerging markets. Investors and industry leaders should watch for the execution of Semicon 2.0 and the commercial adoption rates of sovereign models like BharatGen Param2 as key indicators of India's progress in this high-stakes global race.